Efficient Gradient-Based Inference through Transformations between Bayes Nets and Neural Nets

3 Feb 2014Diederik P. KingmaMax Welling

Hierarchical Bayesian networks and neural networks with stochastic hidden units are commonly perceived as two separate types of models. We show that either of these types of models can often be transformed into an instance of the other, by switching between centered and differentiable non-centered parameterizations of the latent variables... (read more)

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